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AERPAW Find-a-Rover (AFAR) Challenge in December 2023

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Mar 04, 2024 version files 40.54 MB

Abstract

Introduction

In December 2023, the AERPAW Find-a-Rover (AFAR) Challenge marked a significant advancement in the field of unmanned aerial and ground vehicle collaboration. The challenge, hosted by AERPAW (Aerial Experimentation and Research Platform for Advanced Wireless), focused on the integration of cutting-edge technologies in unmanned aerial vehicles (UAVs) and unmanned ground vehicles (UGVs).

Objective of the Challenge

The primary objective of the AFAR Challenge was to demonstrate the capability of UAVs in accurately and swiftly localizing a UGV. Competitors were tasked with utilizing a UAV equipped with a software-defined radio (SDR) to detect and localize the UGV. The SDR on the UAV was designed to continuously receive a specific channel-sounding waveform, as detailed in the GE2 example experiment from the AERPAW user manual.

Technical Specifications and Constraints

  • Waveform Characteristics: The challenge mandated the use of a narrowband waveform with a bandwidth of 125 KHz. Competitors were restricted from altering the waveform parameters at the UGV, ensuring a standardized test environment.
  • Antenna Configuration: The system setup included one transmit antenna and one receiver antenna, with the antenna patterns for both being provided to the participants.
  • Environmental Data: Competitors were also given a geographical map of the environment to aid in the strategic deployment of the UAV.

Challenge Execution

Participants in the challenge had the flexibility to either use fixed waypoints for the UAV or develop their own algorithms for trajectory updates. These algorithms could instruct the UAV on the next waypoint to fly to, based on the observed signal strength received from the UGV.

While the experiments have been executed and the data has been collected by the AERPAW Operations team in the real-world testbed environment, the experiments have been originally developed by the participating teams in AERPAW's digital twin. This public dataset includes data for all teams from both the development environment and the real-world environment. Names of the teams, their corresponding institutions, and the names of the team leads, are as follows.

1) Eagles, University of North Texas (Lead: Jaya Sravani Mandapaka)
2) NYU Wireless, NYU (Lead: Weijie Wang)
3) Team SunLab, University of Georgia (Lead: Paul Kudyba)
4) Team Wolfpack, NC State University (Lead: Cole Dickerson)
5) Daedalic Wings, NC State University (Lead: Baisakhi Chatterjee)